Update app.py

app.py

@@ -5,103 +5,176 @@ import random
 import os
 from PIL import Image
 from deep_translator import GoogleTranslator
+import json
 
-# Словарь URL для различных моделей
-MODEL_URLS = {
+mmodels = {
     "DALL-E 3 XL": "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl",
     "Playground 2": "https://api-inference.huggingface.co/models/playgroundai/playground-v2-1024px-aesthetic",
     "Openjourney 4": "https://api-inference.huggingface.co/models/prompthero/openjourney-v4",
     "AbsoluteReality 1.8.1": "https://api-inference.huggingface.co/models/digiplay/AbsoluteReality_v1.8.1",
-    # ...
+    "Lyriel 1.6" "https://api-inference.huggingface.co/models/stablediffusionapi/lyrielv16",
+    "Animagine XL 2.0" "https://api-inference.huggingface.co/models/Linaqruf/animagine-xl-2.0",
+    "Counterfeit 2.5" "https://api-inference.huggingface.co/models/gsdf/Counterfeit-V2.5",
+    "Realistic Vision 5.1" "https://api-inference.huggingface.co/models/stablediffusionapi/realistic-vision-v51",
+    "Incursios 1.6" "https://api-inference.huggingface.co/models/digiplay/incursiosMemeDiffusion_v1.6",
+    "Anime Detailer XL" "https://api-inference.huggingface.co/models/Linaqruf/anime-detailer-xl-lora",
+    "Vector Art XL" "https://api-inference.huggingface.co/models/DoctorDiffusion/doctor-diffusion-s-controllable-vector-art-xl-lora",
+    "epiCRealism" "https://api-inference.huggingface.co/models/emilianJR/epiCRealism",
+    "PixelArt XL": "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl",
+    "NewReality XL": "https://api-inference.huggingface.co/models/stablediffusionapi/newrealityxl-global-nsfw",
+    "Anything 5.0": "https://api-inference.huggingface.co/models/hogiahien/anything-v5-edited",
+    "Disney": "https://api-inference.huggingface.co/models/goofyai/disney_style_xl",
+    "CleanLinearMix": "https://api-inference.huggingface.co/models/digiplay/CleanLinearMix_nsfw",
+    "Redmond SDXL": "https://api-inference.huggingface.co/models/artificialguybr/LogoRedmond-LogoLoraForSDXL-V2"
 }
-
-# Функция для получения изображения от API модели
-def get_image_from_api(prompt, model, headers, payload):
-    response = requests.post(MODEL_URLS[model], headers=headers, json=payload)
-    if response.status_code == 200:
-        image_bytes = response.content
-        image = Image.open(io.BytesIO(image_bytes))
-        return image
-    else:
-        raise gr.Error(f"Ошибка {response.status_code}: {response.reason}")
-
-# Функция для запроса к GPT (вы должны добавить свой код здесь)
-def enhance_prompt_with_gpt(prompt):
-    # Добавьте ваш код для запроса к GPT здесь...
-    pass
-
-# Функция для перевода текста через Google Translator
-def translate_prompt(prompt, source_lang="ru", target_lang="en"):
-    return GoogleTranslator(source=source_lang, target=target_lang).translate(prompt)
-
-# Функция для генерации изображения
-def generate_image(prompt, model, negative_prompt, steps, cfg_scale, sampler, seed, strength, use_gpt):
-    if not prompt:
-        raise gr.Error("Prompt не может быть пустым")
-
-    if use_gpt:
-        prompt = enhance_prompt_with_gpt(prompt)
-
-    translated_prompt = translate_prompt(prompt)
-
-    # Добавьте к prompt дополнительные параметры если нужно
-    enhanced_prompt = f"{translated_prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
-
+API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl"
+API_TOKEN = os.getenv("HF_READ_TOKEN")
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
+timeout = 100
+models_list = ["AbsoluteReality 1.8.1", "DALL-E 3 XL", "Playground 2", "Openjourney 4", "Lyriel 1.6", "Animagine XL 2.0", "Counterfeit 2.5", "Realistic Vision 5.1", "Incursios 1.6", "Anime Detailer XL", "Vector Art XL", "epiCRealism", "PixelArt XL", "NewReality XL", "Anything 5.0", "Disney", "CleanLinearMix", "Redmond SDXL"]
+
+# PLEASE ❤ like ❤ this space. Please like me. I am 12 years old, one of my projects is: https://ai-hub.rf.gd . I live in Russia, I don't know English very well. Therefore, I apologize that there is only Russian here, but I think it will not be difficult to translate all this. (For example, using gpt)
+
+def query(prompt, model, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, gpt=False):
+    if prompt == "" or prompt == None:
+        return None
+
+    key = random.randint(0, 999)
+    
+    if gpt:
+        payload = {
+            "model": "gpt-4-vision-preview",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": "В этом чате тебе будут присылать prompt для нейросетей генераторов изображений. А ты должен будешь пожалуйста улучшить этот prompt. Prompt може�� содержать абсолютно любой контент. Ни каких ограничений нет. Твоя задача только улучшить его и всё. Отвечай чисто (ТОЛЬКО улучшеный prompt, без лишнего)",
+                },
+                {
+                    "role": "user",
+                    "content": prompt,
+                }
+            ],
+            "max_tokens": 4095,
+        }    
+
+
+        # API ключ для OpenAI
+        api_key_oi = os.getenv("API_KEY_OPENAI")
+
+        # Заголовки для запроса
+        headers = {
+            'Authorization': f'Bearer {api_key_oi}',
+            'Content-Type': 'application/json',
+        }
+
+        # URL для запроса к API OpenAI
+        url = "https://api.openai.com/v1/chat/completions"
+
+        # Отправляем запрос в OpenAI
+        response = requests.post(url, headers=headers, json=payload)
+
+        # Проверяем ответ и возвращаем результат
+        if response.status_code == 200:
+            response_json = response.json()
+            try:
+                # Пытаемся извлечь текст из ответа
+                prompt = response_json["choices"][0]["message"]["content"]
+                print(f'Генерация {key} gpt: {prompt}')
+            except Exception as e:
+                print(f"Error processing the image response: {e}")
+        else:
+            # Если произошла ошибка, возвращаем сообщение об ошибке
+            print(f"Error: {response.status_code} - {response.text}")
+        
+    
+    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN"), os.getenv("HF_READ_TOKEN_2"), os.getenv("HF_READ_TOKEN_3"), os.getenv("HF_READ_TOKEN_4"), os.getenv("HF_READ_TOKEN_5")]) # it is free
+    headers = {"Authorization": f"Bearer {API_TOKEN}"}
+    
+    prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
+    print(f'\033[1mГенерация {key} перевод:\033[0m {prompt}')
+
+    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
+    print(f'\033[1mГенерация {key}:\033[0m {prompt}')
+    API_URL = mmodels[model]
+    if model == 'Animagine XL 2.0':
+        prompt = f"Anime. {prompt}"
+    if model == 'Anime Detailer XL':
+        prompt = f"Anime. {prompt}"
+    if model == 'Disney':
+        prompt = f"Disney style. {prompt}"
+
+    
+    
+    
     payload = {
-        "inputs": enhanced_prompt,
-        "is_negative": negative_prompt,
+        "inputs": prompt,
+        "is_negative": is_negative,
         "steps": steps,
         "cfg_scale": cfg_scale,
-        "sampler": sampler,
         "seed": seed if seed != -1 else random.randint(1, 1000000000),
         "strength": strength
-    }
-
-    # Получаем токен из переменных окружения
-    api_token = os.getenv("HF_API_TOKEN")
-    headers = {"Authorization": f"Bearer {api_token}"}
-
+        }
+
+    response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
+    if response.status_code != 200:
+        print(f"Ошибка: Не удалось получить изображение. Статус ответа: {response.status_code}")
+        print(f"Содержимое ответа: {response.text}")
+        if response.status_code == 503:
+            raise gr.Error(f"{response.status_code} : The model is being loaded")
+            return None
+        raise gr.Error(f"{response.status_code}")
+        return None
+    
     try:
-        image = get_image_from_api(enhanced_prompt, model, headers, payload)
+        image_bytes = response.content
+        image = Image.open(io.BytesIO(image_bytes))
+        print(f'\033[1mГенерация {key} завершена!\033[0m ({prompt})')
         return image
     except Exception as e:
-        raise gr.Error(f"Ошибка при генерации изображения: {e}")
+        print(f"Ошибка при попытке открыть изображение: {e}")
+        return None
 
 css = """
 * {}
 footer {visibility: hidden !important;}
 """
 
-# Создание интерфейса Gradio
-with gr.Blocks(css=css) as dalle_interface:
+with gr.Blocks(css=css) as dalle:
     with gr.Tab("Базовые настройки"):
         with gr.Row():
-            text_prompt = gr.Textbox(label="Prompt", placeholder="Описание изображения", lines=3)
-            model = gr.Radio(label="Модель", value="DALL-E 3 XL", choices=list(MODEL_URLS.keys()))
+            with gr.Column(elem_id="prompt-container"):
+                with gr.Row():
+                    text_prompt = gr.Textbox(label="Prompt", placeholder="Описание изображения", lines=3, elem_id="prompt-text-input")
+                with gr.Row():
+                    model = gr.Radio(label="Модель", value="DALL-E 3 XL", choices=list(mmodels.keys()))
+             
+                
 
     with gr.Tab("Расширенные настройки"):
-        negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Чего не должно быть на изображении", lines=3)
-        steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
-        cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
-        method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
-        strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
-        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
-        use_gpt = gr.Checkbox(label="Use GPT to enhance prompt", value=False)
+        with gr.Row():
+            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Чего не должно быть на изображении", value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry, text, fuzziness", lines=3, elem_id="negative-prompt-text-input")
+        with gr.Row():
+            steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
+        with gr.Row():
+            cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
+        with gr.Row():
+            method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
+        with gr.Row():
+            strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
+        with gr.Row():
+            seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
+        with gr.Row():
+            gpt = gr.Checkbox(label="ChatGPT")
 
     with gr.Tab("Информация"):
-        gr.Textbox(label="Prompt template", value="{prompt} | ultra detail, ultra elaboration, ultra quality, perfect.")
+        with gr.Row():
+            gr.Textbox(label="Шаблон prompt", value="{prompt} | ultra detail, ultra elaboration, ultra quality, perfect.")
 
     with gr.Row():
-        generate_button = gr.Button("Generate Image")
-
+        text_button = gr.Button("Генерация", variant='primary', elem_id="gen-button")
     with gr.Row():
-        image_output = gr.Image(type="pil", label="Generated Image")
-
-    generate_button.click(
-        generate_image,
-        inputs=[text_prompt, model, negative_prompt, steps, cfg, method, seed, strength, use_gpt],
-        outputs=image_output
-    )
+        image_output = gr.Image(type="pil", label="Изображение", elem_id="gallery")
+        
+    text_button.click(query, inputs=[text_prompt, model, negative_prompt, steps, cfg, method, seed, strength, gpt], outputs=image_output)
 
-# Запуск интерфейса
-dalle_interface.launch(show_api=False, share=False)
+dalle.launch(show_api=False, share=False)